1. Field
Example embodiments relate to a method and apparatus for resizing an image using a discrete cosine transform (DCT), for example, for upscaling and/or downscaling an input image to any vertical and/or horizontal resizing ratio.
2. Description of the Related Art
Various methods of compressing image data have been introduced to may attempt to meet the demands of multimedia technologies. Image compression technologies may be widely used in a diverse range of technology fields. For example, image compression may be used in the field of satellite broadcasting to transmit a large amount of data over a channel having a limited transmission band. The current transmission band of one channel allocated for satellite broadcasting is 27 MHz. About 30 to 50 Mbps of data for digital broadcasting may be transmitted in such a transmission band. However, if image compression technology is applied to satellite broadcasting, image data corresponding to the above data transmissions may be transmitted using only a bit rate of 5 Mbps. For example, image compression technology may allow about 6 to 10 programs to be simultaneously transmitted over a transmission band of one channel. Furthermore, the required capacity of supplementary equipment, for example, a memory, for storing data may be reduced using image compression technology. Thus, image compression technology may allow high-quality image data to be stored at reduced cost.
Various image compression methods have been introduced. Widely used conventional image compression methods may include a method of compressing an image using spatial correlation of one image frame, a method of compression an image using temporal correlation between consecutive image frames, and a method of compressing an image using code occurrence probability in image frames are widely used.
FIG. 1 is a block diagram of a conventional method of encoding and decoding an image using spatial correlation.
Referring to FIG. 1, a transmitter 110 may encode an original image and may transmit the encoded image. A DCT unit 120 may transform the original image by performing a discrete cosine transform (DCT). The DCT may be one of an orthogonal transformation scheme, which may be employed by various international standards, for example, joint photographic experts group (JPEG) and motion picture experts group (MPEG). The DCT may be used to minimize data loss for image data compression. For example, if the DCT is performed, entropy may be reduced by concentrating image information in a low frequency domain. Because a dominating portion of image data may be concentrated at the low frequency domain, image data loss may be minimized even if a high frequency domain is lost. Therefore, by performing the DCT, image data may be compressed without sustaining a substantial loss of image information.
A quantizing unit 130 may quantize the transformed image data. A quantization operation may divide orthogonal-transformed frequency components by a quantization step size. If the quantization step size is increased, the compressibility may be increased because all terms may become close to zero, however, larger errors may be produced. If the quantization step size is too small, the compressibility may be decreased.
An entropy encoder 140 may encode the quantized image data. The entropy encoder 140 may assign a short code to a value having higher occurrence probability and may assign a comparatively-longer code to a value having lower occurrence probability, so as to reduce an average code length.
The encoded signal may be transmitted to a receiver 190 over a predetermined communication channel 150. An entropy decoder 160 may decode the encoded signal and a de-quantization unit 170 may de-quantizes the decoded signal.
Because various types and forms of displays are used, the image data may need to be resized according to an aspect ratio supported by a corresponding display that may be used to display the image data. For example, if a personal multimedia player (PMP) that reproduces an image through a 3.5 inch display receives a digital multimedia broadcasting image that is produced for a 7 inch display, the PMP may downscale the size of the received image.
FIG. 2 is a block diagram of a conventional method of resizing an image in a spatial domain.
Referring to FIG. 2, a received image may be decoded to a spatial domain signal. The spatial domain signal may be resized by a spatial interpolation unit 250. For example, a bilinear interpolation or a bicubic interpolation may be used for resizing in a spatial domain.
A larger amount of calculation may be required when performing a discrete cosine transformation (DCT), thus in order to reduce the amount of calculation required, a method of resizing a received signal in a DCT domain may be introduced.
FIG. 3 is a block diagram of a conventional method of resizing an image in a DCT domain. As shown in FIG. 3, for example, an 8×8 input image may be transformed to a 4×4 output image.
Referring to FIG. 3, a 4×4 DCT interpolation unit 310 may directly resize an 8×8 DCT signal in the DCT domain without transforming the 8×8 DCT signal in a spatial domain. In the resizing operation, a method of deleting high frequency coefficients from the input DCT coefficients may be used. For example, only low frequency coefficients of the input DCT coefficients may remain after the resizing operation. A 4×4 inverse-DCT (IDCT) unit 350 may transform the resized image data to a spatial domain signal.
As described above, the amount of calculation required may be reduced by directly resizing the image data in the DCT domain. Further, a peak signal to noise ratio (PSNR) may be improved compared to a conventional method of resizing the image data in the spatial domain.
However, a conventional method of resizing image data in a DCT domain may be applicable only for limited resizing ratios. For example, a conventional method of resizing an image data in a DCT domain may be limited to transform an 8×8 input image to a 4×4 output image or a 2×2 output image only. In order to resize an image into any other desired ratio, a conventional method may require a very complicated structured system for resizing the image data. It may be difficult to apply a higher-speed algorithm in such a conventional method of resizing the image data.
Further, a conventional method of resizing an image data in the DCT domain may only be used when a vertical resizing ratio and a horizontal resizing ratio of the input image are identical.
Accordingly, there may be a demand for developing a method of resizing an image data to any combination of target resizing ratios.